The present application relates to the technical field of computer software technologies, and in particular, to word vector processing. Current natural language processing solutions mostly use a neural network-based architecture. An important basic technology in such an architecture is a word vector. The word vector is a vector for mapping a word to a fixed dimension and represents semantic information of the word. In conventional systems, common word vector generation algorithms are typically designed for English or romance languages such as French and Spanish. Algorithms such as GOOGLE's word vector algorithm, FACEBOOK's n-gram character algorithm, and MICROSOFT's deep neural network algorithm function well for English because of the structure and syntax of the English language. However, when such algorithms are applied to Chinese, word vectors that are generated from Chinese words provide poor results.